R help - Jun 2017 - fitting cosine curve

What I did was to plot your initial values, then plot the smoothed
values and guess the constants. That is, I got an "eyeball" fit to the
smoothed values. As I have described this as "gross cheating" in the
past, you should either split your data, estimate on one subset and
then test on another, or estimate on your data and test on a
replication. If you get pretty much the same values, you can be
reasonably confident that they are reliable.

Jim

On Wed, Jun 21, 2017 at 9:52 AM, lily li <chocold12 at gmail.com>
wrote:
> For example, how do you know the value 0.6, and the frequency within cos?
>
> On Tue, Jun 20, 2017 at 5:49 PM, lily li <chocold12 at gmail.com>
wrote:
>>
>> Thanks, that is cool. But would there be a way that can approximate the
>> curve by trying more starting values automatically?
>>
>> On Tue, Jun 20, 2017 at 5:45 PM, Jim Lemon <drjimlemon at
gmail.com> wrote:
>>>
>>> Hi lily,
>>> You can get fairly good starting values just by eyeballing the
curves:
>>>
>>> plot(y)
>>> lines(supsmu(1:20,y))
>>> lines(0.6*cos((1:20)/3+0.6*pi)+17.2)
>>>
>>> Jim
>>>
>>>
>>> On Wed, Jun 21, 2017 at 9:17 AM, lily li <chocold12 at
gmail.com> wrote:
>>> > Hi R users,
>>> >
>>> > I have a question about fitting a cosine curve. I don't
know how to set
>>> > the
>>> > approximate starting values. Besides, does the method work for
sine
>>> > curve
>>> > as well? Thanks.
>>> >
>>> > Part of the dataset is in the following:
>>> > y=c(16.82, 16.72, 16.63, 16.47, 16.84, 16.25, 16.15, 16.83,
17.41,
>>> > 17.67,
>>> > 17.62, 17.81, 17.91, 17.85, 17.70, 17.67, 17.45, 17.58, 16.99,
17.10)
>>> > t=c(7,  37,  58,  79,  96, 110, 114, 127, 146, 156, 161, 169,
176, 182,
>>> > 190, 197, 209, 218, 232, 240)
>>> >
>>> > I use the method to fit a curve, but it is different from the
real
>>> > curve,
>>> > which can be seen in the figure.
>>> > linFit  <- lm(y ~ cos(t))
>>> > fullFit <- nls(y ~ A*cos(omega*t+C) + B,
>>> > start=list(A=coef(linFit)[1],B=coef(linFit)[2],C=0,omega=.4))
#omega
>>> > cannot
>>> > be set to 1, don't know why.
>>> > co <- coef(fullFit)
>>> > fit <- function(x, a, b, c, d) {a*cos(b*x+c)+d}
>>> > plot(x=t, y=y)
>>> > curve(fit(x, a=co['A'], b=co['omega'],
c=co['C'],d=co['B']), add=TRUE
>>> > ,lwd=2, col="steelblue")
>>> >
>>> > ______________________________________________
>>> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>> > https://stat.ethz.ch/mailman/listinfo/r-help
>>> > PLEASE do read the posting guide
>>> > http://www.R-project.org/posting-guide.html
>>> > and provide commented, minimal, self-contained, reproducible
code.
>>
>>
>

Thanks. I will do a trial first. Also, is it okay to have the datasets that
have only part of the cycle, or better to have equal or more than one
cycle? That is to say, I cannot have the complete datasets sometimes.

On Tue, Jun 20, 2017 at 7:37 PM, Don Cohen <don-r-help at
isis.cs3-inc.com>
wrote:
>
> If you know the period and want to fit phase and amplitude, this is
> equivalent to fitting a * sin + b * cos
>
>  > >>> > I don't know how to set the approximate
starting values.
>
> I'm not sure what you meant by that, but I suspect it's related to
> phase and amplitude.
>
>  > >>> > Besides, does the method work for sine curve as
well?
>
> sin is the same as cos with a different phase
> Any combination of a and b above = c * sin (theta + d) for
> some value of c and d and = e * cos (theta + f) for some value
> of e and f.
> Also for any c,d and for any e,f there is an a,b.
> the c and e are what I'm calling amplitude, the d and f are what
> I'm calling phase.
>
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I'm trying the different parameters, but don't know what the error is:
Error in nlsModel(formula, mf, start, wts) :
  singular gradient matrix at initial parameter estimates

Thanks for any suggestions.

On Tue, Jun 20, 2017 at 7:37 PM, Don Cohen <don-r-help at
isis.cs3-inc.com>
wrote:
>
> If you know the period and want to fit phase and amplitude, this is
> equivalent to fitting a * sin + b * cos
>
>  > >>> > I don't know how to set the approximate
starting values.
>
> I'm not sure what you meant by that, but I suspect it's related to
> phase and amplitude.
>
>  > >>> > Besides, does the method work for sine curve as
well?
>
> sin is the same as cos with a different phase
> Any combination of a and b above = c * sin (theta + d) for
> some value of c and d and = e * cos (theta + f) for some value
> of e and f.
> Also for any c,d and for any e,f there is an a,b.
> the c and e are what I'm calling amplitude, the d and f are what
> I'm calling phase.
>
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